This is a compiled dataset of raw XRR measurements together with corresponding fit parameters, intentionally published to use as training or test data for machine learning models.
All data is provided in an hdf5 file, follwing NeXus convention with respect to the provied metadata in the hdf5 attributes. The datesets have been measured in-situ and therefore there are always stacks of curves that correspond to the diffrent layer thicknesses of the same material on top of $SiO_x$. The measured data is provied under experimental and the corresponding fit parameters under fit. Additional information is collected in metadata.
The follwing model was used:
| Air | |
|---|---|
| layer 1: thicknes, roughness and SLD fitted | |
| $SiO_x$: thicknes, roughness and SLD kept constant for each stack | |
| $Si$: roughness and SLD kept constant |
For all provied fits the q-range during fitting was limited form $q_{min} = 0.0 {\mathring{A}}^{-1}$ to $q_{max} = ?? {\mathring{A}}^{-1}$.
Please consider citing the the folloing publication: ###
The dataset itself can be cited via the zenodo doi ###
Have a look at github ### and zenodo ###. In case you wish to add further data to this repository, please use github pull requests and provide feedback through github issuse.
in the following you find some plots presenting the provided experimental data & fits. Most of the dataset were measured insitu therefor there are many measured XRR curves of the same sample while the thin film was still growing (prepared via OMBD). Use the slider to browse through the stacks of curves.
#prepare jupyter notebook for plots shown below
%run prepare_plot.py
#imports
from silx.io.dictdump import nxtodict #read NeXus hdf5 to python dict
import numpy as np
import pandas as pd
from IPython.display import display
#use same q_range as during fitting
q_fit = np.linspace(0.02,0.15,130,endpoint=False)
#produce plots
for key, ds in nxtodict("xrr_dataset.h5").items():
if "@" not in key: #skip nexus attributes
print("Dataset: ",key)
print("Experimentalists: ",ds["metadata"].pop("Experimentalists","?"))
ds["metadata"].pop("@NX_class", "")
display(pd.DataFrame.from_dict({"Dataset":[key],**ds["metadata"]}))
fig = prepare_figure(ds,q_fit,str(ds["metadata"]["Layer_material"])+" on SiOx")
fig.show()
Dataset: DIP_1 Experimentalists: ['Kowark, Stefan']
| Dataset | Layer_CAS | Layer_formula | Layer_material | Substrate_temperature | Substrate_temperature@unit | instrument | q_max_fit | q_max_fit@unit | year_experiment | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | DIP_1 | 188-94-3 | C32H16 | Diindenoperylene | 303 | K | ESRF, ID10b | 0.15 | 1/Ang | 2005 |
Dataset: DIP_2 Experimentalists: ['Hinderhofer, Alexander']
| Dataset | Layer_CAS | Layer_formula | Layer_material | Substrate_temperature | Substrate_temperature@unit | instrument | q_max_fit | q_max_fit@unit | year_experiment | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | DIP_2 | 188-94-3 | C32H16 | Diindenoperylene | 303 | K | ESRF, ID10b | 0.15 | 1/Ang | 2010 |
Dataset: DIP_3 Experimentalists: ['Lorch, Christopher']
| Dataset | Layer_CAS | Layer_formula | Layer_material | Substrate_temperature | Substrate_temperature@unit | instrument | q_max_fit | q_max_fit@unit | year_experiment | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | DIP_3 | 188-94-3 | C32H16 | Diindenoperylene | 303 | K | SLS, MXX04 | 0.15 | 1/Ang | 2012 |
Dataset: DNTT_PDIF_1to2 Experimentalists: ['Rußegger, Nadine' 'Greco, Alessandro']
| Dataset | Layer_material | instrument | q_max_fit | q_max_fit@unit | year_experiment | |
|---|---|---|---|---|---|---|
| 0 | DNTT_PDIF_1to2 | DNTT PDIF (1:2) | DESY, P08 | 0.15 | 1/Ang | 2021 |
Dataset: DNTT_PDIF_2to1 Experimentalists: ['Rußegger, Nadine' 'Greco, Alessandro']
| Dataset | Layer_material | instrument | q_max_fit | q_max_fit@unit | year_experiment | |
|---|---|---|---|---|---|---|
| 0 | DNTT_PDIF_2to1 | DNTT PDIF (2:1) | DESY, P08 | 0.15 | 1/Ang | 2021 |
Dataset: PDIC5 Experimentalists: ?
| Dataset | Layer_material | Substrate_temperature | Substrate_temperature@unit | q_max_fit | q_max_fit@unit | |
|---|---|---|---|---|---|---|
| 0 | PDIC5 | PDIC5 | 303 | K | 0.15 | 1/Ang |
Dataset: PDIC8 Experimentalists: ?
| Dataset | Layer_material | Substrate_temperature | Substrate_temperature@unit | q_max_fit | q_max_fit@unit | |
|---|---|---|---|---|---|---|
| 0 | PDIC8 | PDIC8 | 303 | K | 0.15 | 1/Ang |
Dataset: PDIC8CN2_DIP_1to1 Experimentalists: ?
| Dataset | Layer_material | Substrate_temperature | Substrate_temperature@unit | q_max_fit | q_max_fit@unit | |
|---|---|---|---|---|---|---|
| 0 | PDIC8CN2_DIP_1to1 | PDIC8CN2 DIP (1:1) | 303 | K | 0.15 | 1/Ang |
Dataset: PEN_1 Experimentalists: ['Dax, Ingrid']
| Dataset | Layer_formula | Layer_material | Substrate_temperature | Substrate_temperature@unit | instrument | q_max_fit | q_max_fit@unit | year_experiment | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | PEN_1 | C22H14 | Pentacene | 300 | K | lab source | 0.15 | 1/Ang | 2021 |
Dataset: PEN_2 Experimentalists: ['Dax, Ingrid']
| Dataset | Layer_formula | Layer_material | Substrate_temperature | instrument | q_max_fit | q_max_fit@unit | year_experiment | |
|---|---|---|---|---|---|---|---|---|
| 0 | PEN_2 | C22H14 | Pentacene | LT | lab source | 0.15 | 1/Ang | 2021 |